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<meta name="description" content="首先看一下源码： 12def where(condition, x=None, y=None):    &apos;&apos;&apos;忽略源码&apos;&apos;&apos;  所以实际上既可以只传第一个参数（后面两个默认为None），也可以传两个或三个参数。 用法1：1np.where(condition, x, y)  这里有一点像Excel中的if()函数。 12345&amp;gt;&amp;gt;&amp;gt; aa = np.arange(10)&amp;gt;&amp;">
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<meta property="og:description" content="首先看一下源码： 12def where(condition, x=None, y=None):    &apos;&apos;&apos;忽略源码&apos;&apos;&apos;  所以实际上既可以只传第一个参数（后面两个默认为None），也可以传两个或三个参数。 用法1：1np.where(condition, x, y)  这里有一点像Excel中的if()函数。 12345&amp;gt;&amp;gt;&amp;gt; aa = np.arange(10)&amp;gt;&amp;">
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          <h1 class="post-title" itemprop="name headline">numpy.where()函数用法：（np.where()）</h1>
        

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        <p>首先看一下源码：</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br></pre></td><td class="code"><pre><span class="line"><span class="function"><span class="keyword">def</span> <span class="title">where</span><span class="params">(condition, x=None, y=None)</span>:</span></span><br><span class="line">    <span class="string">'''忽略源码'''</span></span><br></pre></td></tr></table></figure>

<p>所以实际上既可以只传第一个参数（后面两个默认为None），也可以传两个或三个参数。</p>
<h3 id="用法1："><a href="#用法1：" class="headerlink" title="用法1："></a>用法1：</h3><figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">np.where(condition, x, y)</span><br></pre></td></tr></table></figure>

<p>这里有一点像Excel中的if()函数。</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br></pre></td><td class="code"><pre><span class="line"><span class="meta">&gt;&gt;&gt; </span>aa = np.arange(<span class="number">10</span>)</span><br><span class="line"><span class="meta">&gt;&gt;&gt; </span>np.where(aa,<span class="number">1</span>,<span class="number">-1</span>)</span><br><span class="line">array([<span class="number">-1</span>,  <span class="number">1</span>,  <span class="number">1</span>,  <span class="number">1</span>,  <span class="number">1</span>,  <span class="number">1</span>,  <span class="number">1</span>,  <span class="number">1</span>,  <span class="number">1</span>,  <span class="number">1</span>])  <span class="comment"># 0为False，所以第一个输出-1</span></span><br><span class="line"><span class="meta">&gt;&gt;&gt; </span>np.where(aa &gt; <span class="number">5</span>,<span class="number">1</span>,<span class="number">-1</span>)</span><br><span class="line">array([<span class="number">-1</span>, <span class="number">-1</span>, <span class="number">-1</span>, <span class="number">-1</span>, <span class="number">-1</span>, <span class="number">-1</span>,  <span class="number">1</span>,  <span class="number">1</span>,  <span class="number">1</span>,  <span class="number">1</span>])</span><br></pre></td></tr></table></figure>

<h3 id="用法2："><a href="#用法2：" class="headerlink" title="用法2："></a>用法2：</h3><figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">np.where(condition)</span><br></pre></td></tr></table></figure>

<p>只有条件 (condition)，没有x和y，则输出满足条件 (即非0) 元素的坐标（注意是坐标，不是值）。</p>
<p>坐标以tuple的形式给出，通常原数组有多少维，输出的tuple中就包含几个数组，分别对应符合条件元素的各维坐标。</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br></pre></td><td class="code"><pre><span class="line"><span class="meta">&gt;&gt;&gt; </span>a = np.array([<span class="number">2</span>,<span class="number">4</span>,<span class="number">6</span>,<span class="number">8</span>,<span class="number">10</span>])</span><br><span class="line"><span class="meta">&gt;&gt;&gt; </span>np.where(a &gt; <span class="number">5</span>)             <span class="comment"># 返回索引</span></span><br><span class="line">(array([<span class="number">2</span>, <span class="number">3</span>, <span class="number">4</span>]),)             <span class="comment"># 这是6, 8, 10的坐标</span></span><br><span class="line"><span class="meta">&gt;&gt;&gt; </span>a[np.where(a &gt; <span class="number">5</span>)]              <span class="comment"># 等价于 a[a&gt;5]</span></span><br><span class="line">array([ <span class="number">6</span>,  <span class="number">8</span>, <span class="number">10</span>])</span><br><span class="line"></span><br><span class="line"><span class="meta">&gt;&gt;&gt; </span>np.where([[<span class="number">0</span>, <span class="number">1</span>], [<span class="number">1</span>, <span class="number">0</span>]])</span><br><span class="line">(array([<span class="number">0</span>, <span class="number">1</span>]), array([<span class="number">1</span>, <span class="number">0</span>]))</span><br><span class="line"><span class="string">''' 上面这个有点复杂,[[0,1],[1,0]]的真值为两个1，</span></span><br><span class="line"><span class="string">各自的第一维坐标为[0,1]，第二维坐标为[1,0] 。</span></span><br><span class="line"><span class="string">'''</span></span><br></pre></td></tr></table></figure>
      
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